Prediction of Prognosis of HPV-negative Oral and Oropharyngeal Squamous Cell Carcinoma by Deep Learning Identification and Prediction Model of Cyclin D1 Expression Pattern

doi:10.13701/j.cnki.kqyxyj.2023.04.005

Abstract

Abstract: Objective: To evaluate the relationship between the expression of cyclin D1 and the prognosis of patients with HPV-negative oral squamous cell carcinoma (OSCC) and oropharyngeal squamous cell carcinoma (OPSCC), and to establish the image recognition scoring and survival prediction models based on cyclin D1 expression pattern. Methods: The clinicopathological data of 610 patients with HPV negative OSCC and OPSCC were analyzed retrospectively. The differences of overall survival (OS) rate and progression-free survival (PFS) rate of patients under different evaluation methods of cyclin D1 combining with p16/p53 expression and other factors were compared. The image recognition model to scoring cyclin D1 expression pattern was established by YOLOv5 algorithm. On this basis, the survival prediction model was established by DeepHit and DeepSurv algorithms, respectively. Results: There were three expression patterns of cyclin D1 in OSCC and OPSCC cancer nests. Superior to the expression level scoring method, the expression pattern scoring of cyclin D1 was significantly correlated with the prognosis of patients with OSCC (P<0.0001) and OPSCC (P<0.05). And it was an independent prognostic risk factor in both OSCC (P<0.0001) and OPSCC (P<0.05). Based on cyclin D1 expression pattern score model, the average accuracy of the test sets was (78.48±4.31)%. In OS prediction models established by DeepHit algorithm, the C-index of test set was 0.709±0.019, and in the models established by DeepSurv algorithm, the C-index of test set reached 0.715±0.029. Conclusion: Based on image recognition model of cyclin D1 expression pattern, the survival prediction model has a relatively good prediction effect on OS prognosis of HPV-negative OSCC and OPSCC.

Key words: cyclin D1, oral squamous cell carcinoma, oropharyngeal squamous cell carcinoma, prognosis, deep learning

YANG Ke, SUN Yanan, HU Yaying, LV Yinan, ZHEN Xiaofeng, LI Yiwei, ZHANG Jiali. Prediction of Prognosis of HPV-negative Oral and Oropharyngeal Squamous Cell Carcinoma by Deep Learning Identification and Prediction Model of Cyclin D1 Expression Pattern[J]. Journal of Oral Science Research, 2023, 39(4): 308-315.

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